151 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Chalmers University of Technology
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your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
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of Computer and Network Systems , we design secure, dependable and high-performance computer and communication systems that meet the demands of an increasingly digital and interconnected world. About the
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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technology, driven by high-quality research and education, openness and collaboration. As a Teaching Fellow, you will contribute to this goal through engaging teaching and learning in a collegial and inclusive
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. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026/postdoc
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Engineers. The offices also host computer infrastructure and machine learning/data science/research data management experts, who develop, build, and manage the local and national resources for large-scale
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it effect engagement and learning. For more information about the Akelius Math Learning Lab, see: https://www.chalmers.se/institutioner/mv/akelius-math-learning-lab/ Who we are looking
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deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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metaproteomics approaches Analyzing large-scale multi-omics and clinical datasets to investigate individual metabolic responses to diet. The work includes applying advanced statistical and machine learning methods